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Academic Articles & Research Papers
Showing 17 of 37 academic articles
Vishwa S. Parekh, Michael A. Jacobs • Expert Review of Precision Medicine and Drug Development
(2019)
INTRODUCTION: The radiological reading room is undergoing a paradigm shift to a symbiosis of computer science and radiology using artificial intelligence integrated with machine and deep learning with radiomics to better define tissue chara...
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cc-by-nc-nd
DOI: https://doi.org/10.1080/23808993.2019.1585805
PMC: 6508888
Xing Su, Shan Xue, Fanzhen Liu, Jia Wu et al. • IEEE Transactions on Neural Networks and Learning Systems
(2022)
Detecting a community in a network is a matter of discerning the distinct features and connections of a group of members that are different from those in other communities. The ability to do this is of great significance in network analysis...
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Open Access
DOI: https://doi.org/10.1109/tnnls.2021.3137396
N. Kannaiya Raja, E. Laxmi Lydia, Thumpala Archana Acharya, K. Radhika et al. • IEEE Access
(2023)
In recent years, drones or Unmanned Aerial Vehicles (UAVs) got significant attention among researchers because of their extensive application in commercial applications, border surveillance, etc. As the conventional terrestrial communicatio...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3324068
Ziwei Zhang, Peng Cui, Wenwu Zhu • IEEE Transactions on Knowledge and Data Engineering
(2020)
Deep learning has been shown to be successful in a number of domains, ranging from acoustics, images, to natural language processing. However, applying deep learning to the ubiquitous graph data is non-trivial because of the unique characte...
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Open Access
DOI: https://doi.org/10.1109/tkde.2020.2981333
Samane Esmaelzade Kalkhoran, Seyyed Saeed Ghannadpour • Scientific Reports
(2026)
Abstract Porphyry Cu deposits in the Urmia–Dokhtar magmatic belt constitute important exploration targets, yet the heterogeneous and multi-scale nature of geological, geochemical, and remote sensing data introduces substantial uncertainty i...
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Open Access (DOAJ)
DOI: 10.1038/s41598-026-61085-6
Francis Quintal Lauzon • International Conference on Information Science, Signal Processing and their Applications (ISSPA)
(2012)
Deep learning allows automatically learning multiple levels of representations of the underlying distribution of the data to be modeled. In this work, a specific implementation called stacked denoising autoencoders is explored. We contribut...
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DOI: https://doi.org/10.1109/isspa.2012.6310529
Athanasios S. Voulodimos, Nikolaos D. Doulamis, Anastasios D. Doulamis, Eftychios E. Protopapadakis • Computational Intelligence and Neuroscience
(2018)
Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief ...
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DOI: https://doi.org/10.1155/2018/7068349
PMC: 5816885
Ajay Shrestha, Ausif Mahmood • IEEE Access
(2019)
Deep learning (DL) is playing an increasingly important role in our lives. It has already made a huge impact in areas, such as cancer diagnosis, precision medicine, self-driving cars, predictive forecasting, and speech recognition. The pain...
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Open Access
DOI: https://doi.org/10.1109/access.2019.2912200
Wenqiang Liu, Li Yan, Ningning Ma, Gaozhou Wang et al. • Applied Sciences
(2024)
With the rapid development of deep learning, researchers are actively exploring its applications in the field of industrial anomaly detection. Deep learning methods differ significantly from traditional mathematical modeling approaches, eli...
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Open Access (DOAJ)
DOI: 10.3390/app14020774
John D. Kelleher • The MIT Press eBooks
(2019)
An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vi...
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DOI: https://doi.org/10.7551/mitpress/11171.001.0001
Ian Goodfellow, Yoshua Bengio, Aaron C. Courville • The MIT Press eBooks
(2016)
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human c...
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DOI: https://doi.org/10.1016/b978-0-12-804291-5.00010-6
Kamel Arafet, Rafael Berlanga • Algorithms
(2021)
The generation of electricity through renewable energy sources increases every day, with solar energy being one of the fastest-growing. The emergence of information technologies such as Digital Twins (DT) in the field of the Internet of Thi...
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Open Access (DOAJ)
DOI: 10.3390/a14050156
Vidya Baiju, Akshitha J, Namasiyava Naveen S • European Medical Journal
(2024)
Brain tumours are caused by the abnormal growth of cells in the brain. This occurs mainly due to genetic changes or exposure to X-ray radiation. When the tumours are detected early, they can be removed via surgery. The tumour can be removed...
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Open Access (DOAJ)
DOI: 10.33590/emj/NUUC2196
Mathieu Calvat, Chris Bean, Dhruv Anjaria, Hyoungryul Park et al. • npj Computational Materials
(2025)
Abstract To leverage advancements in machine learning for metallic materials design and property prediction, it is crucial to develop a data-reduced representation of metal microstructures that surpasses the limitations of current physics-b...
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Open Access (DOAJ)
DOI: 10.1038/s41524-025-01770-8
Nishant Shukla • CERN Document Server (European Organization for Nuclear Research)
(2018)
Summary Machine Learning with Tensor Flow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding Tensor Flow with Python. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub forma...
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Changhee Yun, Bomi Eom, Sungjun Park, Chanho Kim et al. • Sensors
(2023)
In the medical field, it is delicate to anticipate good performance in using deep learning due to the lack of large-scale training data and class imbalance. In particular, ultrasound, which is a key breast cancer diagnosis method, is delica...
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Open Access (DOAJ)
DOI: 10.3390/s23052864
Tala Talaei Khoei, Naima Kaabouch • Information
(2023)
Intrusion Detection Systems are expected to detect and prevent malicious activities in a network, such as a smart grid. However, they are the main systems targeted by cyber-attacks. A number of approaches have been proposed to classify and ...
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Open Access (DOAJ)
DOI: 10.3390/info14020103